Invention Grant
US08385632B2 System and method for adapting generic classifiers for object detection in particular scenes using incremental training
有权
用于使用增量训练适应特定场景中的物体检测的通用分类器的系统和方法
- Patent Title: System and method for adapting generic classifiers for object detection in particular scenes using incremental training
- Patent Title (中): 用于使用增量训练适应特定场景中的物体检测的通用分类器的系统和方法
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Application No.: US12791786Application Date: 2010-06-01
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Publication No.: US08385632B2Publication Date: 2013-02-26
- Inventor: Fatih M. Porikli
- Applicant: Fatih M. Porikli
- Applicant Address: US MA Cambridge
- Assignee: Mitsubishi Electric Research Laboratories, Inc.
- Current Assignee: Mitsubishi Electric Research Laboratories, Inc.
- Current Assignee Address: US MA Cambridge
- Agent Gene Vinokur; Dirk Brinkman
- Main IPC: G06K9/00
- IPC: G06K9/00

Abstract:
A generic classifier is adapted to detect an object in a particular scene, wherein the particular scene was unknown when the classifier was trained with generic training data. A camera acquires a video of frames of the particular scene. A model of the particular scene model is constructed using the frames in the video. The classifier is applied to the model to select negative examples, and new negative examples are added to the training data while removing another set of existing negative examples from the training data based on an uncertainty measure. Selected positive examples are also added to the training data and the classifier is retrained until a desired accuracy level is reached to obtain a scene specific classifier.
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